1. Field of the Invention
This invention relates generally to a method and apparatus for controlling a multi-input multi-output process, and more particularly, to a method and apparatus for controlling a multi-input multi-output process which may not be modelled perfectly by the reference model. Such methods and apparatuses are useful in many diverse industrial fields, such as metallurgy, pulp and paper processing, petroleum refining, and chemical and pharmaceutical production.
2. Description of Prior Art
Model reference control system theory, whether it is adaptive or non-adaptive, is finding wide industrial applications in today's environment. Techniques under this framework include Model Algorithmic Control, Dynamic Matrix Control, Inferential Control and Internal Model Control, etc. The major advantages of this control system theory are as follows: both feedfoward and feedback control are incorporated naturally, the limitation on the closed-loop system response can be addressed directly based upon the reference model, and the controller can be designed in a straightforward manner to satisfy the closed-loop stability, zero-offset and constraint requirements. In accordance with the model reference control system theory, the controller is first constructed by inverting the invertible part of the reference model (i.e., the inverse must be stable and physically implementable), then a low pass diagonal filter is added externally to the controller so that the closed-loop system is stable if the controlled process is not modelled perfectly by the reference model (i.e., robust stability).
The foregoing procedure for satisfying the robust stability requirement generally detunes the closed-loop system response substantially if the reference model for the controlled process is ill-conditioned, or the ratio of the maximum singular value over the minimum singular value of the reference model is high. The present invention overcomes the aforementioned difficulty, in the framework of model reference control system theory, so that the optimal response of the closed-loop system with a given bound of model uncertainty, is feasible and easily achieved, while retaining the advantages of model reference control system theory.